class_docstr: The class wrapper the PGL graph, the class involve the funtions to implement struc2vec algorithm.
docstr: The main function to execute the structual random walk 
docstr_tok: ["The","main","function","to","execute","the","structual","random","walk"]
code: def executor_random_walk(self, walk_process_id):
      """
      The main function to execute the structual random walk
      """
      nodes = self.nodes
      random.shuffle(nodes)
      walk_path_all_nodes = []
      for node in nodes:
          walk_path = []
          walk_path.append(node)
          layer = 0
          while len(walk_path) < self.walk_depth:
              prop = random.random()
              if prop < 0.3:
                  node = self.choose_neighbor_alias_method(node, layer)
                  walk_path.append(node)
              else:
                  layer = self.choose_layer_to_walk(node, layer)
          walk_path_all_nodes.append(walk_path)
      return walk_path_all_nodes
  
imports: import argparse
  import math
  import random
  import numpy
  import pgl
  from pgl import graph
  from pgl.graph_kernel import alias_sample_build_table
  from pgl.sample import alias_sample
  from data_loader import EdgeDataset
  from classify import train_lr_model
  from sklearn_classify import train_lr_l2_model
label_desc: Use image node_id 13 for calling the StrucVecGraph obj's underlying member method code with example usage: obj.executor_random_walk(walk_process_id) and returns: walk_path_all_nodes